This paper discusses flood forecasting procedures currently practiced at the Canadian provincial river flood forecast centers. In Canada, each province is responsible for collecting and managing meteorological and hydrometric data (through provincial authorities and/or under Federal/Provincial agreements), developing suitable hydrological models, and providing information about river discharge and water level to the public. In case of an extreme event such as flood or drought, the forecast center is responsible for issuing alerts and supporting provincial emergency management. Due to the large diversity in landscape, weather, and hydrological features across the country, extreme events are triggered by different mechanisms such as snowmelt, heavy rainfall, rain on snow, etc., at different times of the year. Each river forecast center deals with unique challenges in data collection, hydrologic/hydraulic modeling, and flood forecasting. Thus, the focus of the Center in planning for developments and future directions could be significantly different from one province to another. In this paper, the significance of river flood forecasting in Canada, as well as the development in hydrological modelling procedures are highlighted. Moreover, an overview of the current approaches for streamflow/flood forecasting used by the Centers is provided. The content presented here is an outcome of our interaction with the forecast centers. This further resulted in identifying a number of research questions to help bridge the gap between ongoing research and needs of the Centers.

Infrastructures are important facilities in urban areas servicing societies. Failure of these systems could pose a significant threat to the public. Increasing the infrastructure’s reliability is one way to ensure that these facilities preserve their performance during natural hazards such as flooding. In this study, a scheme is proposed for financial resource allocation to waste water treatment plants (WWTPs) with the goal of improving resilience and reliability. For this purpose, after determining which WWTPs’ factors (characteristics) are effective on flood resilience, a multicriteria decision-making approach is used to quantify resilience. Then, factors that could be improved by financial resource allocation are identified to increase resilience. To best allocate the available financial resources to these factors, an optimization routine is proposed. This routine uses the technique for order of preference by similarity to ideal solution method and genetic algorithm, and results in a trade-off curve for each plant. To find the optimal way of allocating financial resources among all WWTPs, a second optimization routine is proposed. Finally, to evaluate the WWTPs’ performance against flooding, reliability is calculated using the load-resistance concept. Fourteen WWTPs in New York City were considered in the case study to test the methodology. Results show that by using optimization tools, financial resources allocation could substantially improve resilience and the reliability of WWTPs. The results also indicate that in evaluating the system’s performance to deal with flooding, reliability and resilience result in compatible findings; however, they measure the performance based on different concepts and enumerations. The proposed methodology can be extended and applied for other infrastructures as well.